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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        Tool Citations

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.27.1

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        This report has been generated by the genotoul-bioinfo/metagwgs analysis pipeline. For information about how to interpret these results, please see the documentation.
        Report generated on 2026-01-20, 02:58 CET based on data in: /data/users/fkurz/metagenomics/output_hifiasm_01/work/0e/13659f09ec4d99d903de497b9606cc

        General Statistics

        Showing 48/48 rows and 10/20 columns.
        Sample NameDupsGCAvg lenMedian lenFailedSeqsN50 (Kbp)Assembly Length (Mbp)ReadsReads mapped% Reads mappedN50 (Kbp)Assembly Length (Mbp)ReadsReads mapped% Reads mappedOrganismContigsBasesCDS
        bc2121
        1.3%
        71.0%
        8494bp
        7499bp
        10%
        0.4M
        110.2Kbp
        55.8Mbp
        0.4M
        0.4M
        98.7%
        0.4M
        0.4M
        98.7%
        NA
        719
        55774258
        52761
        bc2121_select_contigs_size1000
        110.2Kbp
        55.8Mbp
        bc2122
        0.4%
        66.0%
        8548bp
        7499bp
        10%
        0.4M
        161.5Kbp
        193.6Mbp
        0.4M
        0.4M
        96.9%
        0.4M
        0.4M
        96.9%
        NA
        2292
        193627887
        183294
        bc2122_select_contigs_size1000
        161.5Kbp
        193.6Mbp
        bc2123
        0.6%
        67.0%
        9148bp
        8499bp
        10%
        0.4M
        4029.8Kbp
        57.2Mbp
        0.4M
        0.4M
        98.5%
        0.4M
        0.4M
        98.5%
        NA
        322
        57201781
        50763
        bc2123_select_contigs_size1000
        4029.8Kbp
        57.2Mbp
        bc2124
        0.5%
        57.0%
        8919bp
        8499bp
        10%
        0.3M
        136.4Kbp
        130.2Mbp
        0.3M
        0.3M
        98.1%
        0.3M
        0.3M
        98.1%
        NA
        1574
        130178963
        122968
        bc2124_select_contigs_size1000
        136.4Kbp
        130.2Mbp
        bc2125
        1.4%
        51.0%
        5172bp
        4499bp
        20%
        0.7M
        1757.1Kbp
        92.9Mbp
        0.7M
        0.7M
        99.8%
        0.7M
        0.7M
        99.8%
        NA
        293
        92868083
        82744
        bc2125_select_contigs_size1000
        1757.1Kbp
        92.9Mbp
        bc2126
        1.3%
        49.0%
        6066bp
        5499bp
        20%
        0.8M
        2137.2Kbp
        99.2Mbp
        0.8M
        0.8M
        99.4%
        0.8M
        0.8M
        99.4%
        NA
        380
        99162928
        88477
        bc2126_select_contigs_size1000
        2137.2Kbp
        99.2Mbp
        bc2127
        1.0%
        49.0%
        7015bp
        6499bp
        20%
        0.8M
        1161.6Kbp
        112.6Mbp
        0.8M
        0.8M
        99.3%
        0.8M
        0.8M
        99.3%
        NA
        838
        112628831
        99825
        bc2127_select_contigs_size1000
        1161.6Kbp
        112.6Mbp
        bc2128
        1.5%
        47.0%
        6473bp
        6499bp
        20%
        0.6M
        4219.5Kbp
        68.6Mbp
        0.6M
        0.6M
        98.7%
        0.6M
        0.6M
        98.7%
        NA
        918
        68583980
        60741
        bc2128_select_contigs_size1000
        4219.5Kbp
        68.6Mbp
        bc2161
        0.4%
        62.0%
        10379bp
        9499bp
        10%
        0.3M
        1708.4Kbp
        94.9Mbp
        0.3M
        0.3M
        98.5%
        0.3M
        0.3M
        98.5%
        NA
        565
        94907105
        86801
        bc2161_select_contigs_size1000
        1708.4Kbp
        94.9Mbp
        bc2162
        0.3%
        66.0%
        8966bp
        8499bp
        10%
        0.3M
        219.2Kbp
        147.5Mbp
        0.3M
        0.3M
        94.0%
        0.3M
        0.3M
        94.0%
        NA
        1864
        147544231
        133765
        bc2162_select_contigs_size1000
        219.2Kbp
        147.5Mbp
        bc2163
        1.8%
        49.0%
        9016bp
        8499bp
        10%
        0.6M
        430.9Kbp
        59.3Mbp
        0.6M
        0.5M
        98.2%
        0.6M
        0.5M
        98.2%
        NA
        737
        59317418
        56202
        bc2163_select_contigs_size1000
        430.9Kbp
        59.3Mbp
        bc2164
        0.7%
        61.0%
        9746bp
        8499bp
        10%
        0.4M
        336.9Kbp
        49.9Mbp
        0.4M
        0.3M
        97.8%
        0.4M
        0.3M
        97.8%
        NA
        471
        49861994
        46839
        bc2164_select_contigs_size1000
        336.9Kbp
        49.9Mbp
        bc2165
        0.4%
        56.0%
        9835bp
        9499bp
        10%
        0.4M
        1297.4Kbp
        82.6Mbp
        0.4M
        0.4M
        97.5%
        0.4M
        0.4M
        97.5%
        NA
        645
        82588430
        75063
        bc2165_select_contigs_size1000
        1297.4Kbp
        82.6Mbp
        bc2166
        0.4%
        52.0%
        10179bp
        9499bp
        10%
        0.3M
        116.8Kbp
        125.0Mbp
        0.3M
        0.3M
        96.9%
        0.3M
        0.3M
        96.9%
        NA
        1714
        125014080
        111009
        bc2166_select_contigs_size1000
        116.8Kbp
        125.0Mbp
        bc2167
        0.9%
        61.0%
        9207bp
        8499bp
        10%
        0.5M
        3966.6Kbp
        54.7Mbp
        0.5M
        0.5M
        98.7%
        0.5M
        0.5M
        98.7%
        NA
        174
        54717993
        50180
        bc2167_select_contigs_size1000
        3966.6Kbp
        54.7Mbp
        bc2168
        1.8%
        47.0%
        3714bp
        3499bp
        30%
        0.6M
        4074.7Kbp
        38.6Mbp
        0.6M
        0.6M
        99.2%
        0.6M
        0.6M
        99.2%
        NA
        155
        38596496
        33967
        bc2168_select_contigs_size1000
        4074.7Kbp
        38.6Mbp
        bc2169
        0.2%
        65.0%
        8893bp
        8499bp
        20%
        0.4M
        330.1Kbp
        212.8Mbp
        0.4M
        0.4M
        94.7%
        0.4M
        0.4M
        94.7%
        NA
        2345
        212767528
        196311
        bc2169_select_contigs_size1000
        330.1Kbp
        212.8Mbp
        bc2170
        0.5%
        57.0%
        9663bp
        8499bp
        10%
        0.4M
        362.0Kbp
        54.5Mbp
        0.4M
        0.4M
        96.9%
        0.4M
        0.4M
        96.9%
        NA
        596
        54493542
        49494
        bc2170_select_contigs_size1000
        362.0Kbp
        54.5Mbp
        bc2171
        0.6%
        62.0%
        11117bp
        10499bp
        0%
        0.4M
        553.7Kbp
        103.5Mbp
        0.4M
        0.4M
        97.1%
        0.4M
        0.4M
        97.1%
        NA
        773
        103538129
        95745
        bc2171_select_contigs_size1000
        553.7Kbp
        103.5Mbp
        bc2172
        0.7%
        48.0%
        5397bp
        5499bp
        20%
        0.3M
        3588.9Kbp
        64.5Mbp
        0.3M
        0.3M
        97.8%
        0.3M
        0.3M
        97.8%
        NA
        601
        64467974
        57775
        bc2172_select_contigs_size1000
        3588.9Kbp
        64.5Mbp
        bc2173
        0.4%
        52.0%
        10961bp
        10499bp
        10%
        0.4M
        467.0Kbp
        115.0Mbp
        0.4M
        0.4M
        97.7%
        0.4M
        0.4M
        97.7%
        NA
        1018
        115024000
        105128
        bc2173_select_contigs_size1000
        467.0Kbp
        115.0Mbp
        bc2174
        0.3%
        69.0%
        8989bp
        7499bp
        10%
        0.3M
        1032.5Kbp
        87.0Mbp
        0.3M
        0.3M
        97.8%
        0.3M
        0.3M
        97.8%
        NA
        461
        86953530
        75492
        bc2174_select_contigs_size1000
        1032.5Kbp
        87.0Mbp
        bc2175
        0.6%
        46.0%
        3205bp
        3249bp
        30%
        0.1M
        57.1Kbp
        37.3Mbp
        0.1M
        0.1M
        98.4%
        0.1M
        0.1M
        98.4%
        NA
        1093
        37307213
        32385
        bc2175_select_contigs_size1000
        57.1Kbp
        37.3Mbp
        bc2176
        1.6%
        46.0%
        3996bp
        3499bp
        20%
        0.6M
        4064.8Kbp
        37.5Mbp
        0.6M
        0.6M
        99.8%
        0.6M
        0.6M
        99.8%
        NA
        52
        37536778
        32997
        bc2176_select_contigs_size1000
        4064.8Kbp
        37.5Mbp

        FastQC (raw)

        Version: 0.12.1

        Quality control tool for high throughput sequencing data.URL: http://www.bioinformatics.babraham.ac.uk/projects/fastqc

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Created with MultiQC

        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Created with MultiQC

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Created with MultiQC

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Created with MultiQC

        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Created with MultiQC

        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Created with MultiQC

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (e.g. PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Created with MultiQC

        Overrepresented sequences by sample

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        24 samples had less than 1% of reads made up of overrepresented sequences

        Top overrepresented sequences

        Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

        Showing 1/1 rows and 3/3 columns.
        Overrepresented sequenceReportsOccurrences% of all reads
        CAGCCCATAGCACTTGTCCTTCGTTCCCAATTTAGGGAATGGCGTTTGTG
        1
        1182
        0.0113%

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Created with MultiQC

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

        Created with MultiQC

        Quast primary assembly

        This section of the report shows primary assembly metrics.URL: http://quast.bioinf.spbau.ruDOI: 10.1093/bioinformatics/btt086

        Assembly Statistics

        Showing 24/24 rows and 4/4 columns.
        Sample NameN50 (Kbp)L50 (K)Largest contig (Kbp)Length (Mbp)
        bc2121
        110.2Kbp
        0.1K
        8237.0Kbp
        55.8Mbp
        bc2122
        161.5Kbp
        0.2K
        8223.6Kbp
        193.6Mbp
        bc2123
        4029.8Kbp
        0.0K
        8230.6Kbp
        57.2Mbp
        bc2124
        136.4Kbp
        0.1K
        8335.6Kbp
        130.2Mbp
        bc2125
        1757.1Kbp
        0.0K
        6909.6Kbp
        92.9Mbp
        bc2126
        2137.2Kbp
        0.0K
        8226.3Kbp
        99.2Mbp
        bc2127
        1161.6Kbp
        0.0K
        7309.4Kbp
        112.6Mbp
        bc2128
        4219.5Kbp
        0.0K
        8217.1Kbp
        68.6Mbp
        bc2161
        1708.4Kbp
        0.0K
        8227.5Kbp
        94.9Mbp
        bc2162
        219.2Kbp
        0.1K
        8225.0Kbp
        147.5Mbp
        bc2163
        430.9Kbp
        0.0K
        8228.8Kbp
        59.3Mbp
        bc2164
        336.9Kbp
        0.0K
        5858.0Kbp
        49.9Mbp
        bc2165
        1297.4Kbp
        0.0K
        8230.3Kbp
        82.6Mbp
        bc2166
        116.8Kbp
        0.2K
        5333.0Kbp
        125.0Mbp
        bc2167
        3966.6Kbp
        0.0K
        8232.5Kbp
        54.7Mbp
        bc2168
        4074.7Kbp
        0.0K
        6909.6Kbp
        38.6Mbp
        bc2169
        330.1Kbp
        0.1K
        6380.9Kbp
        212.8Mbp
        bc2170
        362.0Kbp
        0.0K
        6974.4Kbp
        54.5Mbp
        bc2171
        553.7Kbp
        0.0K
        5777.9Kbp
        103.5Mbp
        bc2172
        3588.9Kbp
        0.0K
        6908.7Kbp
        64.5Mbp
        bc2173
        467.0Kbp
        0.0K
        7025.3Kbp
        115.0Mbp
        bc2174
        1032.5Kbp
        0.0K
        8282.7Kbp
        87.0Mbp
        bc2175
        57.1Kbp
        0.2K
        288.1Kbp
        37.3Mbp
        bc2176
        4064.8Kbp
        0.0K
        6908.2Kbp
        37.5Mbp

        Number of Contigs

        This plot shows the number of contigs found for each assembly, broken down by length.

        Created with MultiQC

        Reads alignment on unfiltered assembly

        This section reports reads alignement on contigs.URL: http://www.htslib.orgDOI: 10.1093/bioinformatics/btp352

        Flagstat

        This module parses the output from samtools flagstat

        Created with MultiQC

        Quast filtered assembly

        This section of the report shows metrics of the filtered assemblies.URL: http://quast.bioinf.spbau.ruDOI: 10.1093/bioinformatics/btt086

        Assembly Statistics

        Showing 24/24 rows and 4/4 columns.
        Sample NameN50 (Kbp)L50 (K)Largest contig (Kbp)Length (Mbp)
        bc2121_select_contigs_size1000
        110.2Kbp
        0.1K
        8237.0Kbp
        55.8Mbp
        bc2122_select_contigs_size1000
        161.5Kbp
        0.2K
        8223.6Kbp
        193.6Mbp
        bc2123_select_contigs_size1000
        4029.8Kbp
        0.0K
        8230.6Kbp
        57.2Mbp
        bc2124_select_contigs_size1000
        136.4Kbp
        0.1K
        8335.6Kbp
        130.2Mbp
        bc2125_select_contigs_size1000
        1757.1Kbp
        0.0K
        6909.6Kbp
        92.9Mbp
        bc2126_select_contigs_size1000
        2137.2Kbp
        0.0K
        8226.3Kbp
        99.2Mbp
        bc2127_select_contigs_size1000
        1161.6Kbp
        0.0K
        7309.4Kbp
        112.6Mbp
        bc2128_select_contigs_size1000
        4219.5Kbp
        0.0K
        8217.1Kbp
        68.6Mbp
        bc2161_select_contigs_size1000
        1708.4Kbp
        0.0K
        8227.5Kbp
        94.9Mbp
        bc2162_select_contigs_size1000
        219.2Kbp
        0.1K
        8225.0Kbp
        147.5Mbp
        bc2163_select_contigs_size1000
        430.9Kbp
        0.0K
        8228.8Kbp
        59.3Mbp
        bc2164_select_contigs_size1000
        336.9Kbp
        0.0K
        5858.0Kbp
        49.9Mbp
        bc2165_select_contigs_size1000
        1297.4Kbp
        0.0K
        8230.3Kbp
        82.6Mbp
        bc2166_select_contigs_size1000
        116.8Kbp
        0.2K
        5333.0Kbp
        125.0Mbp
        bc2167_select_contigs_size1000
        3966.6Kbp
        0.0K
        8232.5Kbp
        54.7Mbp
        bc2168_select_contigs_size1000
        4074.7Kbp
        0.0K
        6909.6Kbp
        38.6Mbp
        bc2169_select_contigs_size1000
        330.1Kbp
        0.1K
        6380.9Kbp
        212.8Mbp
        bc2170_select_contigs_size1000
        362.0Kbp
        0.0K
        6974.4Kbp
        54.5Mbp
        bc2171_select_contigs_size1000
        553.7Kbp
        0.0K
        5777.9Kbp
        103.5Mbp
        bc2172_select_contigs_size1000
        3588.9Kbp
        0.0K
        6908.7Kbp
        64.5Mbp
        bc2173_select_contigs_size1000
        467.0Kbp
        0.0K
        7025.3Kbp
        115.0Mbp
        bc2174_select_contigs_size1000
        1032.5Kbp
        0.0K
        8282.7Kbp
        87.0Mbp
        bc2175_select_contigs_size1000
        57.1Kbp
        0.2K
        288.1Kbp
        37.3Mbp
        bc2176_select_contigs_size1000
        4064.8Kbp
        0.0K
        6908.2Kbp
        37.5Mbp

        Number of Contigs

        This plot shows the number of contigs found for each assembly, broken down by length.

        Created with MultiQC

        Reads alignment on final assembly

        This section reports reads alignement on contigs.URL: http://www.htslib.orgDOI: 10.1093/bioinformatics/btp352

        Flagstat

        This module parses the output from samtools flagstat

        Created with MultiQC

        Structural annotation

        This section of the report shows structural annotations results. CDS are predicted using Prodigal, rRNA using Barrnap and tRNA using tRNAscan-se.URL: http://www.vicbioinformatics.com/software.prokka.shtmlDOI: 10.1093/bioinformatics/btu153

        Showing 24/24 rows and 6/6 columns.
        Sample NameOrganism# contigs# bases# CDS# rRNA# tRNA
        bc2121
        NA
        719
        55774258
        52761
        93
        387
        bc2122
        NA
        2292
        193627887
        183294
        340
        1406
        bc2123
        NA
        322
        57201781
        50763
        168
        576
        bc2124
        NA
        1574
        130178963
        122968
        175
        756
        bc2125
        NA
        293
        92868083
        82744
        147
        604
        bc2126
        NA
        380
        99162928
        88477
        204
        735
        bc2127
        NA
        838
        112628831
        99825
        238
        855
        bc2128
        NA
        918
        68583980
        60741
        162
        536
        bc2161
        NA
        565
        94907105
        86801
        233
        1034
        bc2162
        NA
        1864
        147544231
        133765
        383
        1531
        bc2163
        NA
        737
        59317418
        56202
        150
        641
        bc2164
        NA
        471
        49861994
        46839
        106
        591
        bc2165
        NA
        645
        82588430
        75063
        174
        878
        bc2166
        NA
        1714
        125014080
        111009
        253
        1225
        bc2167
        NA
        174
        54717993
        50180
        89
        306
        bc2168
        NA
        155
        38596496
        33967
        64
        233
        bc2169
        NA
        2345
        212767528
        196311
        408
        2260
        bc2170
        NA
        596
        54493542
        49494
        183
        674
        bc2171
        NA
        773
        103538129
        95745
        236
        1193
        bc2172
        NA
        601
        64467974
        57775
        111
        488
        bc2173
        NA
        1018
        115024000
        105128
        228
        1225
        bc2174
        NA
        461
        86953530
        75492
        229
        896
        bc2175
        NA
        1093
        37307213
        32385
        52
        219
        bc2176
        NA
        52
        37536778
        32997
        56
        226

        This barplot shows the distribution of different types of features found in each contig.

        Prokka can detect different features:

        • CDS
        • rRNA
        • tmRNA
        • tRNA
        • miscRNA
        • signal peptides
        • CRISPR arrays

        This barplot shows you the distribution of these different types of features found in each contig.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        FastQC (raw)0.12.1

        Bins Counts quality

        Number of bins by quality category, according to MIMAG (Minimum information about a metagenome-assembled genome) standards. "High-quality" refers to genomes with Completeness > 90% and Contamination < 5%. "Medium-quality" for genomes with Completeness > 50% and Contamination < 10%. "Low-quality" for genomes with Completeness < 50%. "High-contamination refers to genomes with Contamination > 10%. Completeness refers to the proportion of presence of universal single-copy “marker” genes within a genome. Single-copy marker genes present multiple times within a recovered genome is used to estimate potential Contamination.

        Created with MultiQC

        Bins Size (bp) quality

        Cumulative length of sequences by quality category (according to the bins quality category in the figure above), according to MIMAG (Minimum information about a metagenome-assembled genome) standards. The "not-binned" part refers to the cumulative length of assemblies contained in unbinned contigs. The x-axis corresponds to the number of sequences (or proportion), the y-axis indicates the samples.

        Created with MultiQC

        Dereplicate bins stats

        Showing 67/67 rows and 8/8 columns.
        genome_idgenome_namecompletenesscontaminationgenome_lengthgenome_N50contig_countsum_numreadssum_meandepth
        bc2121_bin_7
        g__Nocardiopsis
        100.0
        0.1
        6193902.0
        6193902.0
        1.0
        33373.0
        43.4
        bc2121_bin_63
        s__Streptomyces sedi
        55.8
        2.4
        3918290.0
        49132.0
        108.0
        14484.0
        26.1
        bc2122_bin_6
        s__Bacillus velezensis
        100.0
        0.0
        4122426.0
        3976686.0
        6.0
        6313.0
        13.8
        bc2122_bin_12
        s__Curtobacterium sp005490985
        100.0
        0.1
        3448987.0
        3384984.0
        3.0
        111356.0
        277.3
        bc2122_bin_48
        s__Streptomyces albidoflavus
        100.0
        0.3
        6981560.0
        6981560.0
        1.0
        422490.0
        529.7
        bc2123_bin_2
        s__Pantoea dispersa
        100.0
        0.0
        4782465.0
        4029847.0
        2.0
        158249.0
        311.7
        bc2123_bin_16
        s__Methylobacterium radiotolerans
        100.0
        0.5
        6346105.0
        2114621.0
        6.0
        39005.0
        49.4
        bc2124_bin_2
        g__Paenibacillus_D
        100.0
        2.6
        8398052.0
        8335592.0
        3.0
        177352.0
        185.8
        bc2124_bin_7
        s__Nocardiopsis eucommiae
        99.9
        2.5
        5832455.0
        340078.0
        28.0
        11005.0
        17.0
        bc2125_bin_211
        s__Agrobacterium cavarae
        100.0
        0.4
        5588438.0
        2884118.0
        15.0
        548426.0
        662.8
        bc2126_bin_260
        s__Bacillus altitudinis
        100.0
        0.0
        4718293.0
        3740568.0
        9.0
        106200.0
        131.8
        bc2127_bin_1
        s__Leifsonia virtsii
        100.0
        0.0
        3780328.0
        3780328.0
        1.0
        18769.0
        37.7
        bc2127_bin_13
        s__Pseudomonas_B sp913774235
        100.0
        0.0
        5277871.0
        5277871.0
        1.0
        76463.0
        106.9
        bc2128_bin_183
        s__Streptomyces sedi
        50.3
        7.5
        3933189.0
        24062.0
        196.0
        35260.0
        63.4
        bc2161_bin_18
        s__Cellulosimicrobium funkei
        100.0
        0.2
        4310611.0
        1730805.0
        4.0
        5580.0
        11.9
        bc2161_bin_34
        s__Bacillus_A cereus
        100.0
        0.0
        5253794.0
        4363211.0
        3.0
        5545.0
        10.0
        bc2161_bin_58
        g__Microbacterium
        100.0
        0.6
        3868292.0
        1112981.0
        4.0
        4896.0
        11.2
        bc2161_bin_543
        g__Neorhizobium
        100.0
        0.0
        5133775.0
        3897655.0
        2.0
        82957.0
        161.1
        bc2162_bin_34
        s__Pantoea septica
        100.0
        0.0
        4109129.0
        4109129.0
        1.0
        71781.0
        156.3
        bc2162_bin_70
        s__Fontibacillus timonensis
        93.0
        0.0
        5195744.0
        127154.0
        53.0
        2549.0
        4.4
        bc2163_bin_4
        g__Advenella
        100.0
        0.2
        4772892.0
        4772892.0
        1.0
        318986.0
        674.9
        bc2163_bin_5
        g__Bordetella_A
        100.0
        0.6
        5346571.0
        5332979.0
        2.0
        39296.0
        73.1
        bc2163_bin_23
        s__Bacillus safensis
        100.0
        0.0
        3746025.0
        738661.0
        10.0
        3083.0
        7.6
        bc2164_bin_1
        g__Agrococcus
        81.8
        0.1
        2882539.0
        123057.0
        29.0
        1937.0
        6.2
        bc2164_bin_2
        s__Paracoccus alcaliphilus
        100.0
        0.1
        4502301.0
        3353778.0
        4.0
        16334.0
        33.4
        bc2164_bin_14
        s__Brevibacterium sediminis
        100.0
        0.2
        4175564.0
        4175564.0
        1.0
        307945.0
        655.1
        bc2164_bin_186
        g__Brachybacterium
        100.0
        0.1
        4205338.0
        688923.0
        10.0
        162275.0
        363.6
        bc2164_bin_274
        s__Staphylococcus pseudoxylosus
        98.5
        4.9
        3156777.0
        216242.0
        20.0
        290029.0
        826.1
        bc2165_bin_13
        s__Olivibacter sp036959255
        100.0
        0.3
        6381034.0
        6381034.0
        1.0
        285179.0
        485.3
        bc2165_bin_17
        s__Stenotrophomonas maltophilia_G
        100.0
        0.2
        4615726.0
        4615726.0
        1.0
        10307.0
        21.2
        bc2165_bin_37
        s__Agrobacterium tumefaciens_B
        100.0
        0.0
        4782573.0
        2802453.0
        2.0
        78707.0
        158.7
        bc2165_bin_410
        g__Aliihoeflea
        96.0
        6.3
        3811245.0
        265209.0
        30.0
        3919.0
        8.2
        bc2166_bin_6
        s__Mammaliicoccus sciuri
        99.9
        0.3
        2845076.0
        2845076.0
        1.0
        91842.0
        344.9
        bc2166_bin_26
        s__Paenibacillus xylanexedens_B
        100.0
        0.2
        6676475.0
        3573067.0
        2.0
        8284.0
        11.0
        bc2166_bin_685
        g__Pelagibacterium
        65.7
        4.0
        2647491.0
        105691.0
        34.0
        1758.0
        5.2
        bc2167_bin_2
        s__Dermacoccus nishinomiyaensis
        100.0
        1.4
        3081652.0
        3081652.0
        1.0
        14294.0
        38.4
        bc2169_bin_4
        s__Luteimonas abyssi
        99.9
        0.9
        3913286.0
        2513475.0
        3.0
        9695.0
        22.0
        bc2169_bin_12
        s__Achromobacter mucicolens
        100.0
        0.1
        5743142.0
        5743142.0
        1.0
        294737.0
        463.2
        bc2169_bin_14
        g__Pelagibacterium
        100.0
        0.7
        3677180.0
        3677180.0
        1.0
        11038.0
        26.9
        bc2169_bin_27
        g__Aquamicrobium_A
        100.0
        0.0
        4271680.0
        3079928.0
        2.0
        11062.0
        22.4
        bc2169_bin_47
        g__Microbacterium
        100.0
        0.2
        3773626.0
        3773626.0
        1.0
        8736.0
        20.1
        bc2169_bin_63
        s__Enterobacter cloacae
        100.0
        0.0
        4792661.0
        4792661.0
        1.0
        12489.0
        23.5
        bc2169_bin_75
        g__Glycomyces
        97.4
        0.0
        4197026.0
        554814.0
        12.0
        25159.0
        43.0
        bc2169_bin_78
        g__Amoebophilus
        98.3
        0.5
        1792314.0
        1792314.0
        1.0
        4046.0
        20.1
        bc2169_bin_95
        s__Advenella incenata
        67.3
        2.8
        2983136.0
        101726.0
        40.0
        6073.0
        16.9
        bc2169_bin_104
        s__Bordetella sp002261475
        100.0
        0.1
        5330590.0
        1318023.0
        8.0
        24710.0
        39.0
        bc2169_bin_110
        s__Cumulibacter soli
        87.6
        0.7
        3703305.0
        108839.0
        36.0
        4063.0
        10.4
        bc2169_bin_472
        s__Streptomyces bacillaris
        100.0
        0.2
        7469903.0
        2236882.0
        6.0
        85660.0
        96.7
        bc2169_bin_634
        s__Glycomyces sp035765105
        60.8
        0.8
        2161500.0
        81164.0
        34.0
        12850.0
        48.6
        bc2170_bin_248
        s__Priestia megaterium
        100.0
        0.5
        5199724.0
        5062286.0
        3.0
        117987.0
        217.5
        bc2170_bin_348
        s__Paenibacillus polysaccharolyticus
        58.8
        2.3
        4432568.0
        47745.0
        115.0
        3234.0
        5.8
        bc2171_bin_10
        s__Bordetella_A sp002261185
        100.0
        0.1
        5640460.0
        5640460.0
        1.0
        56350.0
        114.1
        bc2171_bin_12
        g__Advenella
        100.0
        0.4
        4650029.0
        4650029.0
        1.0
        12595.0
        28.5
        bc2171_bin_15
        s__Pseudomonas_E berkeleyensis
        100.0
        0.2
        5500779.0
        5500779.0
        1.0
        156779.0
        314.7
        bc2171_bin_31
        s__Stenotrophomonas maltophilia_P
        100.0
        0.0
        4181560.0
        4181560.0
        1.0
        140836.0
        328.1
        bc2171_bin_360
        s__Brucella pseudogrignonensis
        99.7
        0.3
        4267370.0
        1063408.0
        9.0
        9045.0
        16.1
        bc2171_bin_417
        s__Pigmentiphaga kullae
        87.7
        0.7
        5433160.0
        135381.0
        54.0
        2032.0
        4.0
        bc2172_bin_4
        s__Brucella intermedia
        100.0
        0.5
        4699299.0
        2581366.0
        2.0
        17230.0
        22.2
        bc2172_bin_152
        g__Bordetella_B
        100.0
        2.3
        8735238.0
        33853.0
        374.0
        62875.0
        33.5
        bc2173_bin_27
        s__Achromobacter ruhlandii
        100.0
        0.1
        6297642.0
        6297642.0
        1.0
        56907.0
        84.8
        bc2173_bin_29
        g__Advenella
        65.6
        0.1
        3039321.0
        1860994.0
        2.0
        3898.0
        12.5
        bc2173_bin_49
        s__Pseudomonas_E fulva_B
        100.0
        0.1
        5108350.0
        5108350.0
        1.0
        23775.0
        45.3
        bc2173_bin_52
        s__Nocardiopsis flavescens
        100.0
        0.9
        7025281.0
        7025281.0
        1.0
        98295.0
        120.0
        bc2173_bin_60
        g__Bordetella_A
        76.4
        2.5
        4081156.0
        172701.0
        50.0
        2803.0
        6.8
        bc2173_bin_74
        s__Paracoccus onubensis_A
        96.4
        3.3
        4926655.0
        421752.0
        25.0
        3392.0
        6.6
        bc2174_bin_5
        s__Streptomyces olivaceus
        100.0
        0.0
        8285268.0
        8232235.0
        2.0
        1198589.0
        1256.1
        bc2174_bin_286
        g__Brevibacterium
        98.3
        9.6
        4321465.0
        130002.0
        52.0
        5442.0
        11.0

        Bins Quality overview

        Quality of bins in terms of completeness and contamination calculated by Checkm2. The points are colored according to their quality, according to the MIMAG standards defined previously (see Bins Counts quality section). Genomes with the best quality (100\% completeness and 0\% contamination) are located in the lower right corner of the graph.

        Created with MultiQC

        Bins Abundances

        Top 30 most abundant genomes (bins) between all samples are shown here. In order to normalize the different library sizes between samples, values are represented as percentages.

        Created with MultiQC

        metagWGS Software Versions

        metagWGS Software Versions are collected at run time from the software output.URL: https://forge.inrae.fr/genotoul-bioinfo/metagwgs

        metagWGS
        v2.5.0
        Nextflow
        v22.04.0
        Python
        v3.10.8
        FastQC
        v0.12.1
        MetaFlye
        v2.9.6-b1802
        Quast
        v5.3.0
        Minimap2
        v2.24-r1122
        Samtools
        v1.15.1
        Concoct
        v1.1.0
        Metabat2
        v2:2.18;
        Maxbin
        v2.2.7
        Binette
        v1.1.2
        dRep
        v3.5.0
        GTDBTK
        v2.4.0
        tRNAscan-SE
        v2.0.11
        Barrnap
        v0.9
        Prodigal
        v2.6.3